Yueqi Duan

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Total Citations

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About

Yueqi Duan is a leading researcher in 3D computer vision and robotic perception, with a focus on shape assembly and online scene understanding. His major contributions lie in advancing category-level multi-part multi-joint 3D shape assembly, where he pioneered methods that integrate physical assembly processes—such as matching and fitting joints—into geometry reasoning, bridging the gap between virtual modeling and real-world autonomous robotic assembly. This work, published in 2023 and 2024, has garnered 16 citations, highlighting its growing influence in CAD modeling and robotics. Duan also introduced memory-based adapters for online 3D scene perception, enabling real-time processing of streaming RGB-D videos for robotic applications, a significant leap from traditional offline methods that rely on pre-reconstructed 3D geometries. His research addresses critical challenges in autonomous systems, from assembly to dynamic scene interpretation. With a citation count approaching 22 across his top papers, Duan’s work is recognized for its practical impact, offering scalable solutions for robotics and computer-aided design. His achievements underscore a commitment to making 3D perception more adaptive and physically grounded, inspiring further innovation in embodied AI.